Estimating disturbances and model uncertainty in model validation for robust control

— Deterministic approaches to model validation for robust control are investigated. In common deterministic model validation approaches, a trade-off between disturbances and model uncertainty is present, resulting in an ill-posed problem. In this paper, an approach to model validation is presented that attempts to remedy the ill-posedness. By employing accurate, non-parametric, deterministic disturbance models in conjunction with enforcing averaging properties of deterministic disturbances, a novel framework enabling model validation for robust control is obtained. The approach results in a realistically estimated model uncertainty and a disturbance model, and is illustrated in a simulation example.

• Type: Conference
• Year: 2008
• Where: CDC
• Authors: Tom Oomen, Okko Bosgra
• Keywords: CDC 2008, Control Systems, Deterministic, Deterministic Model Validation, Model Validation